Big Data Research

Aims & Scope

The journal aims to promote and communicate advances in big data research by providing a fast and high quality forum for researchers, practitioners and policy makers from the very many different communities working on, and with, this topic.

The journal will accept papers on foundational aspects in dealing with big data, as well as papers on specific Platforms and Technologies used to deal with big data.

To promote Data Science and interdisciplinary collaboration between fields, and to showcase the benefits of data driven research, papers demonstrating applications of big data in domains as diverse as Geoscience, Social Web, Finance, e-Commerce, Health Care, Environment and Climate, Physics and Astronomy, Chemistry, life sciences and drug discovery, digital libraries and scientific publications, security and government will also be considered.

Occasionally the journal may publish whitepapers on policies, standards and best practices.

View Aims & Scope

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Metrics & Ranking

Impact Factor

Year	Value
2025	4.2

SJR (SCImago Journal Rank)

Year	Value
2024	0.914

Quartile

Year	Value
2024	Q1

Journal Rank

Year	Value
2024	5565

Journal Citation Indicator

Year	Value
2024	908

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Abstracting & Indexing

Journal is indexed in leading academic databases, ensuring global visibility and accessibility of our peer-reviewed research.

• Scopus
• Google Scholar
• Web of Science

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Subjects & Keywords

Journal’s research areas, covering key disciplines and specialized sub-topics in Business, Management and Accounting, Computer Science and Decision Sciences, designed to support cutting-edge academic discovery.

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Most Cited Articles

The Most Cited Articles section features the journal's most impactful research, based on citation counts. These articles have been referenced frequently by other researchers, indicating their significant contribution to their respective fields.

• Significance and Challenges of Big Data Research

  Citation: 575

  Authors: Xiaolong, Benjamin W., Xueqi, Yuanzhuo

• Efficient Machine Learning for Big Data: A Review

  Citation: 499

  Authors: Omar Y., Paul D., Sami, George K., Kamal

• Geospatial Big Data: Challenges and Opportunities

  Citation: 335

  Authors: Jae-Gil, Minseo

• Random Forests for Big Data

  Citation: 297

  Authors: Robin, Jean-Michel, Christine, Nathalie

• Big Data Analytics for Dynamic Energy Management in Smart Grids

  Citation: 283

  Authors: Panagiotis D., Vasileios M., George K.

• Demystifying Big Data Analytics for Business Intelligence Through the Lens of Marketing Mix

  Citation: 230

  Authors: Shaokun, Raymond Y.K., J. Leon

• Finding the Best Classification Threshold in Imbalanced Classification

  Citation: 214

  Authors: Quan, Sifa, Ziyu, Meihong, Ying

• Reference Architecture and Classification of Technologies, Products and Services for Big Data Systems

  Citation: 180

  Authors: Pekka, Daniel

• SMR: Medical Knowledge Graph Embedding for Safe Medicine Recommendation

  Citation: 160

  Authors: Fan, Meng, Haofen, Sen, Mengyue

• Deep Learning-Based Weather Prediction: A Survey

  Citation: 151

  Authors: Xiaoli, Xiaoyong, Kaijun, Junqiang, Zichen, Kefeng, Xiang

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